OpenNMT is an open-source toolkit for neural machine translation (NMT). The system prioritizes efficiency, modularity, and extensibility with the goal of supporting NMT research into model architectures, feature representations, and source modalities, while maintaining competitive performance and reasonable training requirements. The toolkit consists of modeling and translation support, as well as detailed pedagogical documentation about the underlying techniques. OpenNMT has been used in several production MT systems, modified for numerous research papers, and is implemented across several deep learning frameworks.
@article{arxiv.1805.11462,
title = {OpenNMT: Neural Machine Translation Toolkit},
author = {Guillaume Klein and Yoon Kim and Yuntian Deng and Vincent Nguyen and Jean Senellart and Alexander M. Rush},
journal= {arXiv preprint arXiv:1805.11462},
year = {2018}
}
Comments
Presentation to AMTA 2018 - Boston. arXiv admin note: substantial text overlap with arXiv:1701.02810